CSIRO PUBLISHING
Marine and Freshwater Research, 2012, 63, 505–512 http://dx.doi.org/10.1071/MF11237
Genetic population structure and connectivity in a commercially exploited and wide-ranging deepwater shark, the leafscale gulper (Centrophorus squamosus) A. Verı´ssimo A,B, J. R. McDowell A and J. E. Graves A A
Virginia Institute of Marine Science, College of William & Mary, PO Box 1346, Gloucester Point, VA 23062, USA. B Corresponding author. Email:
[email protected]
Abstract. The leafscale gulper (Centrophorus squamosus) is a wide-ranging deepwater benthopelagic shark threatened by commercial fisheries in parts of its range. Despite concerns about resource sustainability, little is known about the population structure and connectivity between critical habitats of the leafscale gulper. This study investigates the genetic population structure and the migration patterns of C. squamosus using nuclear microsatellites and mitochondrial NADH dehydrogenase subunit 2 (ND2) gene sequences. Genetic diversity was estimated and compared among sample collections from off Ireland, Portugal, the Azores, South Africa and New Zealand. The null hypothesis of genetic homogeneity among all collections was not rejected by the nuclear loci (FST (the overall genetic differentiation among sample collections) ¼ 0.002, P ¼ 0.88), but we found long-term genetic divergence between New Zealand and the remaining collections at the mtDNA ND2 (FCT (genetic differentation among groups of sample collections) ¼ 0.366, P ¼ 0.000). Migration rate estimates indicated limited female dispersal across the Indian Ocean whereas males showed less restricted dispersal. Our results are consistent with a single genetic stock of C. squamosus and the existence of sexbiased dispersal across the Indian Ocean. Widespread genetic homogeneity at nuclear loci minimizes the loss of unique adaptive genetic diversity in the event of localised depletion. However, high local fishing mortality may have far reaching impacts given the marked sex- and maturity-stage-based habitat partitioning previously reported for C. squamosus. Additional keywords: elasmobranch, top-predator.
Received 28 October 2011, accepted 6 March 2012, published online 13 June 2012
Introduction Deepwater chondrichthyans, i.e. those occurring below 200 m, are a highly diverse group comprising about half (,46%) of the known sharks, skates, rays and chimaeras (Kyne and Simpfendorfer 2010). The limited data available on the general biology and ecology of these taxa suggest life history strategies characterised by low lifetime fecundities, slow growth rates, late age at maturity and high longevities (Kyne and Simpfendorfer 2010). Consequently, deepwater chondrichthyans are assumed to have long population doubling times (e.g. decades to centuries) and, thus, to be highly vulnerable to population depletion (Garcı´a et al. 2008; Simpfendorfer and Kyne 2009; Kyne and Simpfendorfer 2010). During the last several decades, fishing effort has moved away from shallow coastal regions into progressively deeper reaches of the world’s oceans (Morato et al. 2006) and many species of deepwater chondrichthyans have become exploited by deepwater fisheries around the globe (see Kyne and Simpfendorfer 2010 for examples). Due to their life history strategies, which are highly conserved, some of these species have already shown signs of localised declines in abundance (e.g. Graham et al. 2001). One Journal compilation Ó CSIRO 2012
such example is the leafscale gulper, Centrophorus squamosus, a medium-sized (,1.5 m) benthopelagic squaloid shark regularly taken in several mixed deepwater trawl and longline fisheries off the eastern North Atlantic (ICES 2010). In recent years, the abundance of C. squamosus in this region has been considered depleted and a zero fishing mortality has been advised since 2006 (ICES 2010). Despite the current concerns about resource sustainability, there is limited information on the biology, ecology, or population structure of C. squamosus, which may limit the efficacy of current management efforts. The leafscale gulper has a wide but patchy distribution along the eastern Atlantic, western Indian and western Pacific oceans (Compagno et al. 2005), where it is usually found on continental and insular slopes between 300 and 1500 m (Clarke et al. 2001a, 2001b). The reproductive mode of C. squamosus is yolk-sac viviparity with fecundity ranging between one and 10 pups per litter (Figueiredo et al. 2008; Severino et al. 2009). Sexual maturation is reached at a large size (.80% of maximum size in both sexes; Clarke et al. 2001a; Ban˜o´n et al. 2006; Figueiredo et al. 2008) and at ages of 20 years in males and 30–40 years in females (Clarke et al. 2002). www.publish.csiro.au/journals/mfr
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The available data regarding population structure of C. squamosus is mostly restricted to the eastern North Atlantic, where fishery catch data suggest habitat partitioning according to sex and maturity stage. Commercial catches are comprised mostly of mature males, with a small fraction of immature fish and even smaller numbers of mature females (Clarke et al. 2001a; Ban˜o´n et al. 2006; Figueiredo et al. 2008). Pregnant females have seldom been reported and only off the Iberian Peninsula, Madeira and the Canary Islands (Ban˜o´n et al. 2006; Figueiredo et al. 2008; Severino et al. 2009; Pajuelo et al. 2010). The location of nursery/pupping areas is also unknown but immature fish appear to recruit to the major fishing grounds on continental slope waters as they approach sexual maturity (i.e. .80 cm total length). The spatial segregation of Centrophorus squamosus according to sex and maturity stage within the eastern North Atlantic suggests that individuals are part of the same population unit and undergo extensive migrations between critical habitats. Dispersal in deepwater benthopelagic sharks, like C. squamosus, may be facilitated by the presence of continuous continental and insular slope habitats but may be limited across open oceanic waters. Recent studies in other deepwater benthopelagic sharks have provided some support for this hypothesis. High genetic homogeneity among locations in the eastern Atlantic and western Indian ocean was found for the Portuguese dogfish, Centroscymnus coelolepis, suggesting high genetic connectivity between adjacent ocean basins connected by continuous slope waters (Verı´ssimo et al. 2011). Weak but significant genetic differentiation between Chilean and New Zealand samples was reported for the southern lantern shark (Etmopterus granulosusi), suggesting that gene flow may be limited across the South Pacific (Straube et al. 2011). Nevertheless, the sampling design in these studies did not allow testing for the presence of gene flow across open ocean waters in C. coelolepis, or along continuous slope waters in E. granulosus. Effective conservation and management hinges on sound knowledge of population structure and connectivity between critical habitats. Such knowledge is essential for the delimitation of adequate management units and the determination of the patterns and levels of migration among geographic regions and populations. Our study aimed to investigate the pattern of population structure and connectivity in C. squamosus using
nuclear microsatellite loci and nucleotide sequences of the mitochondrial DNA ND2 gene. Specifically, we tested the null hypothesis of genetic homogeneity (no genetic structure) at different spatial scales: (1) across all sampled locations (i.e. widespread panmixia); (2) within the eastern North Atlantic, as suggested by the catch distribution data; (3) between adjacent ocean basins connected by continuous continental slopes, i.e. eastern North Atlantic and western Indian; and (4) between oceans separated by open ocean waters, i.e. eastern North Atlantic/western Indian and western South Pacific. The data were also used to infer the existence of sex-biased dispersal in C. squamosus by comparing the patterns of genetic diversity distribution exhibited by nuclear (biparentally inherited) and mitochondrial markers (maternally inherited). Materials and methods Sample collection and DNA extraction Tissue samples (fin clips or muscle) were collected from leafscale gulpers caught by commercial fishing vessels and scientific research cruises with either deepwater longlines or trawls. Samples were obtained from several locations throughout the species’ range including three locations in the eastern North Atlantic – off west Ireland (IRE), mainland Portugal (POR) and over the mid-Atlantic ridge north of the Azores (MAR), one location in the western Indian off eastern South Africa (SA) and one location in the western South Pacific off north-west New Zealand (NZ). The total length of sampled specimens ranged between 47 and 144 cm and varied among collection sites (Table 1). Mature males and immature females were sampled in IRE, POR and MAR, whereas mature males and females in all maturity stages were sampled in SA and NZ. All tissue samples were preserved in 20% dimethyl sulfoxide buffer saturated with NaCl (Seutin et al. 1991) and stored at room temperature. Genomic DNA (gDNA) was extracted using the Qiagen DNeasy Tissue kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions. Genetic analysis A fragment of the mtDNA NADH dehydrogenase subunit 2 (ND2) gene region was amplified for each individual fish via the polymerase chain reaction (PCR) in 25 mL reactions containing
Table 1. Genetic diversity indices and sample collection details for the leafscale gulper (Centrophorus squamosus) Sex-ratio (percent females sampled, %F); TL range, minimum–maximum total length (mean total length); N, number of individuals sampled; Ho: observed mean heterozygosity; FIS, inbreeding coefficient; A, mean number of alleles; RS, mean allelic richness; H, number of haplotypes (unique haplotypes); h, haplotype diversity; p, nucleotide diversity; k, mean number of nucleotide differences between haplotypes
Ireland (IRE)A Portugal (POR)B South Africa (SA)A Azores (MAR)B New Zealand (NZ)A A B
Sex-ratio (%F)
TL range (cm) (mean)
N
Ho
FIS
A
RS
N
H
h
p
k
0.17 0.38 0.73 0.00 0.82
57–116 (103.5) 93–140 (108.6) 95–144 (117.3) 102–119 (108.8) 47–142 (104.9)
48 48 47 45 40
0.74 0.76 0.77 0.73 0.75
0.014 0.020 0.025 0.040 0.030
11.5 13.3 (4) 13.8 (10) 12.7 (6) 13 (2)
11.0 12.6 13.0 12.2 12.9
44 46 44 39 42
9 (4) 9 8 9 (3) 7 (3)
0.47 0.48 0.40 0.41 0.50
0.0015 0.0014 0.0020 0.0011 0.0017
0.93 0.81 1.23 0.66 1.02
Fishing gear used in sample collection, trawl. Fishing gear used in sample collection, longline.
Nuclear microsatellites
Mitochondrial ND2 sequences
Genetic population structure in Centrophorus squamosus
10–20 ng gDNA, 1 mM of each primer (ND2_F 50 TTCCTCA CACAAGCAACCGC 30 ; ND2_R 50 GATGGTGGCTGGGA TGGC 30 ), 200 mM each dNTP, 5 mg of bovine serum albumin (BSA), 0.025 units Taq polymerase, 1 Taq buffer with 1.5 mM MgCl2 (Qiagen) and autoclaved ultra-pure water. PCR conditions consisted of an initial denaturation of 5 min at 948C, followed by 45 cycles of 1 min at 948C, 35 s at 588C, 1 min at 728C and a final extension step of 5 min at 728C. Amplicons were cleaned with the QIAquick PCR Purification Kit (Qiagen) according to the manufacturer’s protocol. Forward strands were sequenced using the ABI Big Dye Terminator Cycle Sequencing Kit (Applied Biosystems, Warrington, UK) and reactions were run on an ABI Prism 3130xl genetic analyser (Applied Biosystems). The resulting DNA sequences were imported into Sequencher ver. 4.8 (Gene Codes Corp., Ann Harbor, MI, USA) and checked for quality and accuracy in nucleotide base assignment. All sequences were aligned in MacVector ver. 8.0 (MacVector Inc., Cary, NC, USA) using ClustalW multiple alignment algorithm (Thompson et al. 1994). Haplotypes were confirmed by sequencing the reverse strand of one individual for each unique haplotype, following the above procedures. Individual fish were genotyped at six nuclear microsatellite loci (see Table S1, available as Supplementary Material to this paper), of which four loci (CsquMx31, CsquMx59, CsquMx104, CsquGT64; GenBank accession numbers JQ037909–JQ037912) were developed from libraries generated using the biotinylated probes (GT)12 and Mix 4 (Glenn and Schable 2005). Primers were designed using MacVector 8.1.2 (MacVector Inc.) or Primer3 (Rozen and Skaletsky 2000). Two additional loci, SacaGA11 (Verı´ssimo et al. 2011) and Saca7551, were successfully cross-amplified with primers designed for Squalus acanthias. All six loci were initially screened for polymorphisms and subsequently tested for consistent amplification and conformation to Hardy-Weinberg equilibrium (HWE). Microsatellite loci were amplified via PCR in 5 mL reactions containing 5–15 ng of gDNA, 0.0375 mM of forward primer with an added T3 tail, 0.15 mM of reverse primer, 0.1 mM of fluorescently labelled T3 primer (e.g. PET, VIC, or 6FAM), 0.025 units Taq DNA polymerase (Qiagen), 0.2 mM each dNTP, 1.5 mM MgCl2, 1 mg BSA, 1 Taq buffer (Qiagen) and autoclaved ultrapure water. PCR conditions consisted of an initial denaturation of 3 min at 948C, followed by 35–45 cycles of 1 min at 948C, 35–60 s at the corresponding annealing temperature (see Supplemental Table S1 for details) and 35–60 s at 728C and a final extension step for 7 min at 728C. The products were run on an ABI Prism 3130xl (Applied Biosystems). Genotypes were scored manually with the software GeneMarker ver. 1.3 (Softgenetics, LLC, State College, PA, USA) and the presence of null alleles and scoring errors were tested for each locus using Micro-Checker ver. 2.2.0.3 (van Oosterhout et al. 2004). Tests for HWE for each locus within each sample collection and for linkage disequilibrium between each pair of loci within and among all collections were calculated in Genepop ver. 4.0 (Raymound and Rousset 1995; Rousset 2008). Analysis of genetic diversity Standard microsatellite and mitochondrial ND2 diversity indices were calculated using FSTAT ver. 2.9.3.2 (Goudet 2002) and DnaSP ver. 5 (Librado and Rozas 2009) (Table 1).
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A haplotype network was constructed in Network ver. 4.5.1.0 (Fluxus Technology, Suffolk, England) in which distinct haplotypes are positioned according to their overall similarity and their geographic occurrence can be superimposed to highlight spatial patterns in haplotype distribution. The network was constructed using the maximum parsimony approach of Polzin and Daneschmand (2003) and the median joining algorithm of Bandelt et al. (1999), with default parameters and a transition to transversion ratio of 4 : 1 (estimated from the data). Analysis of genetic divergence and population structure Levels of between-population genetic differentiation were estimated in Arlequin ver. 3.5.1.2 (Excoffier and Lischer 2010) using pairwise FST tests based on allele frequency differences at the nuclear microsatellite loci and pairwise FST values based on a genetic distance matrix of pairwise differences for the mtDNA ND2 haplotypes. The corresponding P-values were estimated from 10 000 permutations of alleles/haplotypes between sample collections (Excoffier et al. 1992). Since the value of FST and its analogues (e.g. FST) are upper-bounded by the withinpopulation homozygosity value (Jost 2008), direct comparisons and interpretations of pairwise genetic differences obtained with markers exhibiting different levels of genetic diversity (e.g. nuclear microsatellites and mitochondrial genes) are difficult. To correct for inter-marker differences in genetic diversity we estimated pairwise values of Jost’s Dest (Jost 2008) between sample collections. Estimates of Dest were obtained for the nuclear microsatellite loci using the harmonic mean of the distances across loci implemented in SMOGD (Crawford 2010) and for the mtDNA ND2 fragment using the method described by Jost (2008). The different scenarios of genetic population structure outlined in the introduction were evaluated for each marker type through an analysis of molecular variance (AMOVA), as implemented in Arlequin. For microsatellite data, the AMOVA was based on allelic frequencies and performed for each locus independently as well as across loci. For mtDNA sequence data, the AMOVA was based on a genetic distance matrix of pairwise differences. In either case, significance was estimated by 10 000 permutations of the data (Excoffier et al. 1992). Estimates of genetic connectivity and divergence time among populations The software MDIV (Nielsen and Wakeley 2001) was used to infer the joint estimates of scaled divergence time (t ¼ divergence time/(2 effective population size)) and scaled migration rates (M ¼ (2 effective population size migration rate)) between genetically different populations, using mtDNA ND2 sequence data. Runs were performed using the HKY model of sequence evolution (Hasegawa et al. 1985) with lengths of 2 106 steps with 5 105 steps of burn-in. Convergence of estimates was evaluated by performing multiple runs using different random seeds and using different prior intervals. Levels of genetic connectivity among populations were investigated by estimating the historical migration rates (Mi-j ¼ migration rate/mutation rate per generation) from population i to population j, using the maximum likelihood approach implemented in MIGRATE-n ver. 3.2.7 (Beerli 1998; Beerli and Felsenstein 1999, 2001). The microsatellite and mitochondrial
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datasets were run independently to compare the patterns produced by each marker type. Preliminary runs were performed with default start parameters to test for adequacy of run and burn-in lengths and to estimate the start parameters for subsequent runs. The final runs for microsatellite genotypes used 10 short chains for a total of 2 106 visited genealogies (104 recorded steps), one long chain of 4 106 visited genealogies (105 recorded steps) and a burn-in of 105 steps. The final runs for the mtDNA data used 10 short chains of 20 106 visited genealogies (104 recorded steps) and one long chain of 20 106 visited genealogies (105 recorded steps) with a burn-in of 5 104 steps. The adaptive (four chains) and static (five chains) heating schemes were used to adequately explore the parameter space for the microsatellite and mitochondrial datasets, respectively. The consistency of parameter estimates was checked by using different start parameters and run lengths, as well as running replicate runs. Results Genetic diversity Individual multilocus genotypes were obtained for 228 leafscale gulpers at six nuclear microsatellite loci, in which three individuals were successfully genotyped at only five loci. The total number of alleles per microsatellite locus varied between five
33% 83% 50%
Fig. 1. Maximum parsimony haplotype network of the mtDNA ND2 of the leafscale gulper Centrophorus squamosus. Haplotypes (n ¼ 21) are represented by circles with sizes proportional to the absolute frequency in the total sample. Branch lengths correspond to one nucleotide substitution between haplotypes except where indicated by the number of black bars. Support values of connections were 100% except where noted. Colour code: orange, Ireland; red, Portugal; brown, South Africa; green, MAR; white, NZ.
and 55 (mean s.d.: 19.0 18.5) and the observed heterozygosity per locus ranged between 0.48 and 0.90 (0.74 0.18). There were no significant deviations of genotypic distributions from HWE expectations and there was no evidence of linkage disequilibrium among loci. Also, no allele scoring errors or null alleles were detected for any of the loci. The mean allelic richness within samples varied between 11.0 and 13.0 whereas the mean observed heterozygosity varied between 0.73 and 0.77. A 602-bp fragment of the mtDNA ND2 gene region was amplified for 215 C. squamosus samples. The final alignment of individual nucleotide sequences showed a total of 26 mutations and 21 distinct haplotypes (GenBank accession numbers JQ035532–JQ035655). The overall nucleotide and haplotype diversities were 0.0018 and 0.574 respectively. The maximum parsimony haplotype network of the mtDNA ND2 region had a star-shaped conformation with one very common and ubiquitous central haplotype and several low-frequency, derived haplotypes (Fig. 1). Haplotype and nucleotide diversities found in each sample collection ranged between 0.40 and 0.50 and between 0.0011 and 0.0020 respectively (Table 1). IRE, POR, MAR and SA were dominated by the central haplotype (H2; 72–77% of the individuals), whereas NZ was dominated by a derived haplotype exclusive to this location (H17; 69% of the individuals). IRE, MAR and NZ had three exclusive haplotypes each whereas POR and SA shared all haplotypes with two or more sample collections. Genetic divergence and population structure Standard FST values indicated no significant genetic differentiation among collections at the nuclear microsatellite loci (Table 2). At the mtDNA ND2 gene region, no differentiation was found among collections from the eastern North Atlantic and western Indian oceans (i.e. IRE, POR, MAR and SA), but NZ was significantly different from all collections (Table 2). Pairwise comparisons including the NZ collection showed genetic differentiation values 1–2 orders of magnitude higher than comparisons among eastern North Atlantic (i.e. IRE, POR, MAR) and SA collections. These results are consistent with those obtained with Dest tests, indicating that marker-specific diversity levels did not bias the overall pattern of genetic differentiation among sample collections. The hypothesis of genetic homogeneity among all sampled locations (i.e. considering all collections in one group) was not rejected by the nuclear data. No significant heterogeneity was observed either when using all loci combined (FST ¼ 0.001,
Table 2. Levels of genetic divergence between populations of Centrophorus squamosus Below diagonal: pairwise FST values and Jost’s Dest values based on nuclear microsatellites in parentheses. Above diagonal: pairwise FST values and Jost’s Dest values based on mtDNA ND2 nucleotide sequences in parentheses. Significant P-values after Bonferroni correction are indicated: *, P , 0.005 Nuclear microsatellites
mtDNA ND2 IRE
IRE POR SA MAR NZ
0.002 (0.000) 0.002 (0.000) 0.003 (0.000) 0.004 (0.000)
POR
SA
MAR
NZ
0.001 (0.006)
0.009 (0.010) 0.005 (0.004)
0.002 (0.009) 0.000 (0.004) 0.004 (0.000)
0.001 (0.001) 0.002 (0.000)
0.323 (0.732)* 0.357 (0.732)* 0.388 (0.732)* 0.371 (0.734)*
0.004 (0.000)
0.002 (0.000) 0.003 (0.000) 0.002 (0.000)
Genetic population structure in Centrophorus squamosus
P ¼ 0.919) or when considering each locus separately (FST range: 0.005 to 0.001, P: 0.325–0.861). In contrast, strong genetic divergence among collections was found at the mtDNA ND2 locus (FST ¼ 0.185, P ¼ 0.000). When comparing only eastern North Atlantic samples (i.e. including IRE, POR and MAR in one group), the null hypothesis of genetic homogeneity was not rejected by either the mitochondrial (FST ¼ 0.003, P ¼ 0.611) or the nuclear microsatellite datasets (combined loci FST ¼ 0.002, P ¼ 0.883; FST range: 0.005 to 0.001, P ¼ 0.420–0.833). Likewise, the hypothesis of genetic homogeneity between the eastern North Atlantic and the western Indian collections (i.e. considering IRE, POR, MAR and SA in the same group) was also not rejected by the mitochondrial (FST ¼ 0.0001, P ¼ 0.451) or nuclear datasets (combined loci FST ¼ 0.001, P ¼ 0.821; FST range: 0.005 to 0.001, P ¼ 0.306–0.762). Based on the above result, all eastern North Atlantic and the western Indian collections were included in one group hereafter designated as the Atlantic/Indian group. Comparisons of the Atlantic/Indian group against NZ produced conflicting results with the different marker types. High genetic divergence was found between the two groups at the mtDNA ND2 (FCT ¼ 0.366, P ¼ 0.000) but genetic homogeneity between the groups was not rejected by the nuclear loci (combined loci FST ¼ 0.003, P ¼ 0.917; FST range: 0.007 to 0.002, P ¼ 0.328–0.870). Estimates of genetic connectivity and divergence time among populations The genetic connectivity and divergence time among populations was investigated considering an Atlantic/Indian group and NZ. Estimates of scaled divergence time (T) and scaled migration rate (M) between groups obtained with MDIV and based on mtDNA ND2 data, showed that T-N, i.e. the likelihood of T increased with increasing divergence time, and that M ¼ 0.9 (95% confidence interval (CI): 0.50–3.15). The estimation of historical migration rates using the full mtDNA dataset in MIGRATE-n did not converge (i.e. estimates were not consistent between runs), even when several different length runs, start parameters and heating schemes were tested. The observed lack of convergence and inconsistency in posterior parameter distributions between runs may be due to the existence of different migration events/periods (with potentially distinct rate values) having different regions of higher likelihood within the parameter space. Specifically, two temporally-spaced migration events are apparent from the haplotype network: an older event suggested by the sharing of two highly derived, low frequency haplotypes (H1 and H4) between Atlantic/Indian and NZ groups and a relatively more recent event suggested by the sharing of a less derived, low frequency haplotype (H7). Therefore, we ran MIGRATE-n on two subsets of mtDNA data, both of which achieved convergence and consistency among runs. Dataset 1 included all haplotypes except H7 and comprised the older migration event, whereas dataset 2 included all haplotypes except H1 and H4 and represented the recent migration event. Dataset 1 recovered similar migration rate estimates in both directions (MAt/I-NZ: 97.1, 95% CI: 52.7–160.7; MNZ-At/I: 115.5, 95% CI: 62.8–198.8), whereas dataset 2 showed comparatively lower rates from the Atlantic/Indian to NZ
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(MAt/I-NZ: 58.0, 95% CI: 30.0–99.6) and little to no migration on the opposite direction (MNZ-At/I: 0.00, 95% CI: 0.00–11.8). Historical migration rate estimates based on the nuclear microsatellite genotypes were MAt/I-NZ: 2.03 (95% CI: 1.76–2.34) and MNZ-At/I: 4.13 (95% CI: 3.65–4.70). Discussion Genetic diversity distribution and population structure The genetic diversities of Centrophorus squamosus nuclear loci were high in each sample collection as evidenced by high values of allelic richness and mean observed heterozygosity (Table 1). The observed levels of variability at the nuclear microsatellite loci are within the range reported in several other elasmobranch taxa (see Schmidt et al. 2009; for a comparative analysis). In contrast, the mtDNA ND2 gene region had low overall haplotype and nucleotide diversities and each sample collection was dominated by a single haplotype (Fig. 1). Low levels of genetic diversity at mitochondrial loci are not uncommon in elasmobranchs, but the reasons for the limited variability are still under debate (Martin and Palumbi 1993; Martin 1999). Despite the difference in the overall levels of variability between marker types, the genetic diversity indices varied little among collections of C. squamosus, indicating that each location had similar amounts of the overall diversity found in the species. Within the eastern North Atlantic, the genetic diversity present at nuclear and mitochondrial markers was equally distributed among sample collections (e.g. IRE, POR, MAR) resulting in low and non-significant genetic differentiation values between each pair of collections (Table 2). The null hypothesis of genetic homogeneity was not rejected when all eastern North Atlantic collections were included in one group. These results indicate that individuals within the above region belong to the same genetic stock, in agreement with previous studies suggesting that leafscale gulpers caught off western Europe are part of the same population unit based on evidence of complex habitat use involving migration between critical habitats (Clarke et al. 2001a; Ban˜o´n et al. 2006; Figueiredo et al. 2008). At a larger geographic scale, the comparisons of eastern North Atlantic collections of C. squamosus with the western Indian Ocean collection (e.g. SA) indicated no significant genetic differentiation between any pairwise comparisons of collections, regardless of marker type (Table 2). Moreover, the AMOVA did not reject the hypothesis of genetic homogeneity between an eastern North Atlantic group and SA, indicating that gene flow is occurring or has occurred until recently between the Atlantic and Indian oceans. This is a remarkable result considering the large geographic distance separating eastern North Atlantic and SA collections (several thousands of km) and the fact that dispersal in elasmobranchs is achieved solely by active swimming (Musick et al. 2004). The apparent genetic homogeneity observed between eastern North Atlantic and SA is in line with our initial expectation that the presence of continuous continental slope waters off the western coasts of Europe and Africa may facilitate dispersal in this deepwater benthopelagic shark. However, the exchange of a few individual migrants per generation is enough to homogenise the gene pool of two distantly located populations (Waples 1998). In the case of
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C. squamosus, the long generation time of the species (,30 years; Clarke et al. 2002) may allow enough time for such long-distance movements to occur in every generation. In contrast to the above results, strong genetic differentiation was detected at the mtDNA ND2 gene region between NZ and the other sample collections, suggesting long-term isolation between the Atlantic/Indian group and NZ (i.e. T tended to infinity, Nielsen and Wakeley 2001) in the presence of limited migration. However, no genetic divergence was detected at the nuclear loci, a result that is consistent with ongoing or recent gene flow among all sampling locations. Despite the opposite patterns of genetic divergence exhibited by the mitochondrial and the nuclear markers, both marker types support the existence of migration between the Atlantic/Indian and western South Pacific oceans. As mentioned earlier, C. squamosus has not been reported to occur in the northern Indian Ocean continental slope (Compagno et al. 2005), which would provide a potentially suitable connecting pathway between the western Indian and western Pacific oceans. Thus, migration between the above two regions is likely to take place across the open waters of the southern Indian Ocean, in contrast to our initial expectations. Records of C. squamosus individuals caught in the upper 1250 m of oceanic waters deeper than 4000 m (Last and Stevens 2009) lend additional support to the possibility that the species is capable of pelagic movement. Genetic connectivity and population divergence The migration rates of C. squamosus between the Atlantic/ Indian group and NZ estimated with the mitochondrial and nuclear datasets were different after correcting for markerspecific mutation rates (,1010 per year per mitochondrial genome in elasmobranchs, Martin et al. 1992; 102 to 105 per microsatellite locus per generation, Ellegren 2000) and for generation time (,30 years in C. squamosus, Clarke et al. 2002). Nuclear-based migration rates were high, on the order of 105 to 102 per generation, whereas mitochondrial-based migration rates were lower, ranging from 0–106 per generation. Because of the different mode of inheritance of the nuclear (biparentally inherited) and mitochondrial genomes (maternally inherited), estimates of migration based on nuclear markers are reflective of the most dispersive sex, whereas those based on mitochondrial markers deal exclusively with female-mediated dispersal (Heist 2004). Accordingly, migration rate estimates for female C. squamosus are lower than those estimated for males. Given the long divergence time between the Atlantic/Indian and NZ groups, the low levels of female-mediated gene flow across the Indian Ocean may have been insufficient to counteract divergence at the mtDNA locus. In contrast, the higher male-mediated migration rates may have been enough to effectively homogenise genetic diversity at the nuclear loci among all locations. The contrasting migration rate estimates between male and female C. squamosus and the striking inter-marker differences in the levels of genetic divergence across the Indian Ocean (up to two orders of magnitude difference) suggest the existence of sexbiased dispersal. Genetic differentiation between populations is expected to be higher at the mtDNA locus in species where females are phylopatric or have limited dispersal compared with males (Prugnolle and de Meeus 2002). Previous studies in other widely distributed elasmobranchs have also found high levels of
A. Verı´ssimo et al.
male-mediated gene flow, resulting in genetic homogeneity at nuclear loci between oceans, whereas females showed comparatively stronger genetic structure across similar spatial scales based on mtDNA data. These patterns have been attributed to female phylopatry to discrete geographic regions (e.g. nursery areas) in other elasmobranch species such as the shortfin mako Isurus oxyrinchus (Schrey and Heist 2003) and the sandbar shark Carcharhinus limbatus (Portnoy et al. 2010). Therefore, the significant genetic divergence of C. squamosus across the Indian Ocean based on the mtDNA ND2 region may be associated with long-term female phylopatry to the Atlantic/Indian oceans and to the western South Pacific Ocean (NZ), with males exhibiting comparatively less restricted dispersal. According to the above results, the overall pattern of genetic population structure in C. squamosus is characterised by genetic homogeneity at the nuclear microsatellite loci throughout the eastern North Atlantic, western Indian and western South Pacific oceans and by strong genetic divergence at the mtDNA ND2 gene between the Atlantic/Indian and NZ. From an evolutionary perspective, individuals belonging to the same population exhibit the same genetic composition as a result of random mating and gene flow (Waples and Gaggiotti 2006). Since the nuclear genome contains most of the adaptive genetic variation and is, thus, the carrier of the evolutionary potential for adaptation to environmental change (Allendorf and Luikart 2007), populations should be defined according to the presence or absence of nuclear gene flow (Portnoy 2010). In this context, our results indicate the existence of a single genetic stock, i.e. a single population, of C. squamosus encompassing all sampled regions and including two main breeding areas on either side of the Indian Ocean. Female phylopatry to the Atlantic/ Indian and NZ does not imply reproductive isolation between the regions, since highly dispersive males maintain gene flow. The paucity of studies investigating the population structure and connectivity in deepwater elasmobranchs and the high diversity of forms and life strategies of these taxa severely limit our ability to compare and extrapolate the patterns described for C. squamosus to other species. However, we can hypothesise that other deepwater taxa, particularly other Centrophorus species, may have similar long-distance dispersal potential and may sustain moderate to high levels of genetic connectivity among distant geographic regions. For instance, genetic homogeneity was found for the Portuguese dogfish (Centroscymnus coelolepis) along the eastern Atlantic (Verı´ssimo et al. 2011) and for the thorny skate (Amblyraja radiata) along the North Atlantic (Chevolot et al. 2007). Deviations from the hypothesis of widespread genetic homogeneity in deepwater elasmobranchs are associated with the presence of potential physical barriers to gene flow leading to population differentiation. For instance, the genetic differentiation between Chilean and New Zealand collections of the southern lantern shark (Etmopterus granulosus) (Straube et al. 2011) suggest that the open oceanic waters of the South Pacific may limit gene flow. Other physical barriers may be found at relatively smaller geographic scales, like the shallow Gibraltar Strait separating Atlantic and Mediterranean populations of the longnose skate (Dipturus oxyrinchus) (Griffiths et al. 2011), or even the temperature and salinity gradient separating Baltic and North Sea populations of A. radiata (Chevolot et al. 2007).
Genetic population structure in Centrophorus squamosus
Implications for fisheries management and conservation The genetic homogeneity observed at the nuclear loci of leafscale gulper collections separated by thousands of miles minimises the loss of unique genetic diversity in the event of localised depletion (e.g. off Ireland), as other regions (e.g. South Africa) may have a genetic composition similar to the one in the depleted region. This is an important consideration since conserving the adaptive genetic variation contained in the nuclear genome directly translates to the maintenance of the evolutionary potential of a species and its long-term survival. However, as mentioned above, genetic homogeneity among distant locations can be maintained by only a few individual migrants per generation (Waples 1998). Therefore, genetic connectivity does not necessarily equate to demographic connectivity and low levels of migration among locations are likely to be insufficient to compensate localised declines in abundance. The existence of distinct breeding areas in C. squamosus also has important management and conservation implications. Recruitment within the Atlantic/Indian and NZ depends almost exclusively on phylopatric females, since female-mediated dispersal across the Indian Ocean is limited. Severe declines in abundance within a given breeding area, e.g. due to overexploitation, will compromise recruitment on the long-term even in the presence of high levels of male-mediated migration. Thus, each breeding area should be considered an independent demographic unit for management and conservation purposes. Furthermore, the spatial segregation observed in C. squamosus implies that different locations may harbor distinct components of the same population unit (e.g. small juveniles, mature males, or mature/pregnant females). Consequently, high mortality rates (e.g. due to fishing) in a geographically circumscribed region may have far reaching implications, as recruitment success and the long-term sustainability of the whole population may be compromised. Future studies should aim at providing detailed information about the size and sexual maturity composition of C. squamosus throughout its range to more accurately determine the scale of demographic connectivity among locations, as well as to uncover potential mating and nursery areas of increased conservation value. Acknowledgements The authors are thankful to all individuals and institutions who assisted with sample collection and to those who contributed information or provided comments on the manuscript: G. Johnston (Marine Institute); C. Cotton, J. Musick and K. Reece (VIMS); G. Menezes (DOP-UAc¸); J. Leopoldo and J. Po´lvora (Quivari-Cac¸a˜o); R. Leslie (MCM); D. Stevens and R. O’Driscoll (NIWA). We would also like to thank the two anonymous reviewers and the editor for their careful revision of the manuscript and their insightful comments and suggestions, which have greatly improved the quality of the paper. A. Verı´ssimo was funded by the Fulbright Commission PhD scholarship 2005/ 2006 and by Fundac¸a˜o para a Cieˆncia e Tecnologia (SFRH/BD/40326/2007). This is contribution number 3222 of the Virginia Institute of Marine Science.
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